English

Computing eigenvalues of semi-infinite quasi-Toeplitz matrices

Numerical Analysis 2022-08-17 v2 Numerical Analysis

Abstract

A quasi-Toeplitz (QT) matrix is a semi-infinite matrix of the form A=T(a)+EA=T(a)+E where T(a)T(a) is the Toeplitz matrix with entries (T(a))i,j=aji(T(a))_{i,j}=a_{j-i}, for ajiCa_{j-i}\in\mathbb C, i,j1i,j\ge 1, while EE is a matrix representing a compact operator in 2\ell^2. The matrix AA is finitely representable if ak=0a_k=0 for k<mk<-m and for k>nk>n, given m,n>0m,n>0, and if EE has a finite number of nonzero entries. The problem of numerically computing eigenpairs of a finitely representable QT matrix is investigated, i.e., pairs (λ,v)(\lambda,{\bf v}) such that Av=λvA{\bf v}=\lambda {\bf v}, with λC\lambda\in\mathbb C, v=(vj)jZ+{\bf v}=(v_j)_{j\in\mathbb Z^+}, v0{\bf v}\ne 0, and j=1vj2<\sum_{j=1}^\infty |v_j|^2<\infty. It is shown that the problem is reduced to a finite nonlinear eigenvalue problem of the kind WU(λ)β=0 WU(\lambda){\pmb \beta}=0, where WW is a constant matrix and UU depends on λ\lambda and can be given in terms of either a Vandermonde matrix or a companion matrix. Algorithms relying on Newton's method applied to the equation detWU(λ)=0\det WU(\lambda)=0 are analyzed. Numerical experiments show the effectiveness of this approach. The algorithms have been included in the CQT-Toolbox [Numer. Algorithms 81 (2019), no. 2, 741--769].

Keywords

Cite

@article{arxiv.2203.06484,
  title  = {Computing eigenvalues of semi-infinite quasi-Toeplitz matrices},
  author = {D. A. Bini and B. Iannazzo and B. Meini and J. Meng and L. Robol},
  journal= {arXiv preprint arXiv:2203.06484},
  year   = {2022}
}
R2 v1 2026-06-24T10:11:06.632Z